def run():
pdb_str="""
CRYST1 5.000 5.000 5.000 90.00 90.00 90.00 P 1
HETATM 1 C C 1 0.000 0.000 0.000 1.00 5.00 C
END
"""
xrs = iotbx.pdb.input(source_info=None, lines=pdb_str).xray_structure_simple()
###
fc = xrs.structure_factors(d_min = 0.26, algorithm = "direct").f_calc()
fft_map_ref = fc.fft_map(resolution_factor = 0.1)
fft_map_ref.apply_sigma_scaling()
map_data_ref = fft_map_ref.real_map_unpadded()
r_r, rho_r = map_1d(xrs=xrs,
map_data=map_data_ref.deep_copy()/flex.max(map_data_ref))
F_0 = xrs.structure_factors(d_min=1.4999999, algorithm="direct").f_calc()
#
fft_map_0 = miller.fft_map(
crystal_gridding = fft_map_ref,
fourier_coefficients = F_0)
fft_map_0.apply_sigma_scaling()
map_data_0 = fft_map_0.real_map_unpadded()
r_s, rho_s = map_1d(xrs=xrs, map_data=map_data_0)
sc = scale(rho_r, rho_s)
rho_s = rho_s*sc
#
R = r_factor(x=r_s, r1=rho_r, r2=rho_s)
cc = flex.linear_correlation(x = rho_r, y = rho_s).coefficient()
print("Initial dist: %6.3f"%R, cc)
### Exercise fixed lam
lam = 0.74
for start_map in ["flat", "lde", "min_shifted"]:
m = mem.run(f=F_0, f_000=xrs.f_000(), lam=lam, resolution_factor=0.1,
verbose=False, start_map=start_map, max_iterations=1300,
detect_convergence=False)
r_m, rho_m = map_1d(xrs=xrs, map_data=m.rho)
sc = scale(rho_r, rho_m)
rho_m = rho_m*sc
R = r_factor(x=r_s, r1=rho_r, r2=rho_m)
cc = flex.linear_correlation(x = rho_r, y = rho_m).coefficient()
print(m.show(verbose=False), "*", "dist: %6.3f"%R, cc)
assert R < 0.0004, R
assert cc > 0.999, R
### Exercise auto-incremented lam, 1
m = mem.run(f=F_0, f_000=xrs.f_000(), lam=0.01, resolution_factor=0.1,
lambda_increment_factor = 1.01, beta=0.5, verbose=True,
start_map="min_shifted", max_iterations=800, detect_convergence=True)
r_m, rho_m = map_1d(xrs=xrs, map_data=m.rho)
sc = scale(rho_r, rho_m)
rho_m = rho_m*sc
R = r_factor(x=r_s, r1=rho_r, r2=rho_m)
cc = flex.linear_correlation(x = rho_r, y = rho_m).coefficient()
print(m.show(verbose=False), "*", "dist: %6.3f"%R, cc)
assert R < 0.004, R
assert cc > 0.999, R
### Exercise auto-incremented lam, 2
m = mem.run(f=F_0, f_000=xrs.f_000(), lam=0.01, resolution_factor=0.1,
lambda_increment_factor = 1.01, beta=0.5, xray_structure=xrs, verbose=True,
start_map="min_shifted", max_iterations=800, detect_convergence=True)
r_m, rho_m = map_1d(xrs=xrs, map_data=m.rho)
sc = scale(rho_r, rho_m)
rho_m = rho_m*sc
R = r_factor(x=r_s, r1=rho_r, r2=rho_m)
cc = flex.linear_correlation(x = rho_r, y = rho_m).coefficient()
print(m.show(verbose=False), "*", "dist: %6.3f"%R, cc)
assert R < 0.05, R
assert cc > 0.998, R
#
of = open("gp","w")
assert rho_r.size() == rho_s.size() == rho_m.size()
for r, r1, r2, r3 in zip(r_r, rho_r, rho_s, rho_m):
print("%15.12f %15.12f %15.12f %15.12f"%(r, r1, r2, r3), file=of)
of.close()
#
m.write_mtz_file()
#
print("gnuplot command to show results:")
print("""
plot [-3:3] [-0.1:1.1] "gp" using 1:2 with lines title "exact" lw 3, "gp" using 1:3 with lines title "synthesis" lw 3 lc rgb "black", "gp" using 1:4 with lines title "MEM" lw 3
""")
def run(args, log):
timer = user_plus_sys_time()
format_usage_message(log=log)
if (len(args) == 0): return
parsed = master_params()
inputs = mmtbx.utils.process_command_line_args(args=args,
master_params=parsed,
log=log)
params = inputs.params.extract()
broadcast(m="Input parameters", log=log)
inputs.params.show(prefix=" ")
###
xray_structure = None
if (len(inputs.pdb_file_names) > 0):
broadcast(m="Input model", log=log)
assert len(inputs.pdb_file_names) == 1
print >> log, " file name:", inputs.pdb_file_names[0]
xray_structure = iotbx.pdb.input(
file_name=inputs.pdb_file_names[0]).xray_structure_simple()
assert xray_structure is not None
xray_structure.show_summary(prefix=" ", f=log)
mmtbx.utils.setup_scattering_dictionaries(
scattering_table=params.scattering_table,
xray_structure=xray_structure,
d_min=0.25)
xray_structure.scattering_type_registry().show(prefix=" ", out=log)
###
broadcast(m="Input reflection data", log=log)
reff = inputs.reflection_file_names
if (len(reff) > 1):
raise Sorry("One reflection file should be provided.")
elif (len(reff) == 0):
if (params.hkl_file_name is None):
raise Sorry("No reflection file provided.")
else:
reff = [params.hkl_file_name]
map_coeffs = reflection_file_utils.extract_miller_array_from_file(
file_name=reff[0], label=params.label, type="complex", log=log)
assert map_coeffs is not None
map_coeffs.show_comprehensive_summary(prefix=" ", f=log)
###
broadcast(m="MEM calculations begin", log=log)
f_000 = params.f_000
solvent_fraction = params.solvent_fraction
if (f_000 is None):
f_000_obj = mmtbx.utils.f_000(
xray_structure=xray_structure,
unit_cell_volume=map_coeffs.unit_cell().volume(),
solvent_fraction=params.solvent_fraction,
mean_solvent_density=params.mean_solvent_density)
f_000 = f_000_obj.f_000
solvent_fraction = f_000_obj.solvent_fraction
print >> log, "F(0,0,0): %12.6f" % f_000
if (solvent_fraction is not None):
print >> log, "solvent_fraction: %6.4f" % solvent_fraction
result = mem.run(f=map_coeffs,
f_000=f_000,
lam=params.lam,
lambda_increment_factor=params.lambda_increment_factor,
resolution_factor=params.resolution_factor,
verbose=True,
start_map="min_shifted",
max_iterations=params.max_iterations,
use_modification=True,
beta=params.beta,
convergence_at_r_factor=params.convergence_at_r_factor,
xray_structure=xray_structure,
convergence_r_threshold=params.convergence_r_threshold,
log=log)
###
broadcast(m="Output MEM map coefficients", log=log)
ind = max(0, reff[0].rfind("."))
ofn = params.output_file_name
if (ofn is None):
ofn = reff[0] + "_mem.mtz" if ind == 0 else reff[0][:ind] + "_mem.mtz"
print >> log, " Output file name:", ofn
result.write_mtz_file(file_name=ofn,
column_root_label=params.column_root_label,
d_min=params.output_high_resolution)
broadcast(m="All done", log=log)
return os.path.abspath(ofn)
def run():
pdb_str="""
CRYST1 5.000 5.000 5.000 90.00 90.00 90.00 P 1
HETATM 1 C C 1 0.000 0.000 0.000 1.00 5.00 C
END
"""
xrs = iotbx.pdb.input(source_info=None, lines=pdb_str).xray_structure_simple()
###
fc = xrs.structure_factors(d_min = 0.26, algorithm = "direct").f_calc()
fft_map_ref = fc.fft_map(resolution_factor = 0.1)
fft_map_ref.apply_sigma_scaling()
map_data_ref = fft_map_ref.real_map_unpadded()
r_r, rho_r = map_1d(xrs=xrs,
map_data=map_data_ref.deep_copy()/flex.max(map_data_ref))
F_0 = xrs.structure_factors(d_min=1.4999999, algorithm="direct").f_calc()
#
fft_map_0 = miller.fft_map(
crystal_gridding = fft_map_ref,
fourier_coefficients = F_0)
fft_map_0.apply_sigma_scaling()
map_data_0 = fft_map_0.real_map_unpadded()
r_s, rho_s = map_1d(xrs=xrs, map_data=map_data_0)
sc = scale(rho_r, rho_s)
rho_s = rho_s*sc
#
R = r_factor(x=r_s, r1=rho_r, r2=rho_s)
cc = flex.linear_correlation(x = rho_r, y = rho_s).coefficient()
print "Initial dist: %6.3f"%R, cc
### Exercise fixed lam
lam = 0.74
for start_map in ["flat", "lde", "min_shifted"]:
m = mem.run(f=F_0, f_000=xrs.f_000(), lam=lam, resolution_factor=0.1,
verbose=False, start_map=start_map, max_iterations=1300,
detect_convergence=False)
r_m, rho_m = map_1d(xrs=xrs, map_data=m.rho)
sc = scale(rho_r, rho_m)
rho_m = rho_m*sc
R = r_factor(x=r_s, r1=rho_r, r2=rho_m)
cc = flex.linear_correlation(x = rho_r, y = rho_m).coefficient()
print m.show(verbose=False), "*", "dist: %6.3f"%R, cc
assert R < 0.0004, R
assert cc > 0.999, R
### Exercise auto-incremented lam, 1
m = mem.run(f=F_0, f_000=xrs.f_000(), lam=0.01, resolution_factor=0.1,
lambda_increment_factor = 1.01, beta=0.5, verbose=True,
start_map="min_shifted", max_iterations=800, detect_convergence=True)
r_m, rho_m = map_1d(xrs=xrs, map_data=m.rho)
sc = scale(rho_r, rho_m)
rho_m = rho_m*sc
R = r_factor(x=r_s, r1=rho_r, r2=rho_m)
cc = flex.linear_correlation(x = rho_r, y = rho_m).coefficient()
print m.show(verbose=False), "*", "dist: %6.3f"%R, cc
assert R < 0.004, R
assert cc > 0.999, R
### Exercise auto-incremented lam, 2
m = mem.run(f=F_0, f_000=xrs.f_000(), lam=0.01, resolution_factor=0.1,
lambda_increment_factor = 1.01, beta=0.5, xray_structure=xrs, verbose=True,
start_map="min_shifted", max_iterations=800, detect_convergence=True)
r_m, rho_m = map_1d(xrs=xrs, map_data=m.rho)
sc = scale(rho_r, rho_m)
rho_m = rho_m*sc
R = r_factor(x=r_s, r1=rho_r, r2=rho_m)
cc = flex.linear_correlation(x = rho_r, y = rho_m).coefficient()
print m.show(verbose=False), "*", "dist: %6.3f"%R, cc
assert R < 0.05, R
assert cc > 0.998, R
#
of = open("gp","w")
assert rho_r.size() == rho_s.size() == rho_m.size()
for r, r1, r2, r3 in zip(r_r, rho_r, rho_s, rho_m):
print >> of, "%15.12f %15.12f %15.12f %15.12f"%(r, r1, r2, r3)
of.close()
#
m.write_mtz_file()
#
print "gnuplot command to show results:"
print """
def run(args, log):
timer = user_plus_sys_time()
format_usage_message(log = log)
if(len(args)==0): return
parsed = master_params()
inputs = mmtbx.utils.process_command_line_args(
args=args, master_params=parsed, log=log)
params = inputs.params.extract()
broadcast(m="Input parameters", log = log)
inputs.params.show(prefix=" ")
###
xray_structure = None
if(len(inputs.pdb_file_names)>0):
broadcast(m="Input model", log = log)
assert len(inputs.pdb_file_names) == 1
print >> log, " file name:", inputs.pdb_file_names[0]
xray_structure = iotbx.pdb.input(
file_name = inputs.pdb_file_names[0]).xray_structure_simple()
assert xray_structure is not None
xray_structure.show_summary(prefix=" ", f=log)
mmtbx.utils.setup_scattering_dictionaries(
scattering_table = params.scattering_table,
xray_structure = xray_structure,
d_min = 0.25)
xray_structure.scattering_type_registry().show(prefix=" ", out = log)
###
broadcast(m="Input reflection data", log = log)
reff = inputs.reflection_file_names
if(len(reff) > 1):
raise Sorry("One reflection file should be provided.")
elif(len(reff) == 0):
if(params.hkl_file_name is None):
raise Sorry("No reflection file provided.")
else: reff = [params.hkl_file_name]
map_coeffs = reflection_file_utils.extract_miller_array_from_file(
file_name = reff[0],
label = params.label,
type = "complex",
log = log)
assert map_coeffs is not None
map_coeffs.show_comprehensive_summary(prefix=" ", f=log)
###
broadcast(m="MEM calculations begin", log = log)
f_000 = params.f_000
solvent_fraction = params.solvent_fraction
if(f_000 is None):
f_000_obj = mmtbx.utils.f_000(
xray_structure = xray_structure,
unit_cell_volume = map_coeffs.unit_cell().volume(),
solvent_fraction = params.solvent_fraction,
mean_solvent_density = params.mean_solvent_density)
f_000 = f_000_obj.f_000
solvent_fraction = f_000_obj.solvent_fraction
print >> log, "F(0,0,0): %12.6f"%f_000
if(solvent_fraction is not None):
print >> log, "solvent_fraction: %6.4f" % solvent_fraction
result = mem.run(
f = map_coeffs,
f_000 = f_000,
lam = params.lam,
lambda_increment_factor = params.lambda_increment_factor,
resolution_factor = params.resolution_factor,
verbose = True,
start_map = "min_shifted",
max_iterations = params.max_iterations,
use_modification = True,
beta = params.beta,
convergence_at_r_factor = params.convergence_at_r_factor,
xray_structure = xray_structure,
convergence_r_threshold = params.convergence_r_threshold,
log = log)
###
broadcast(m="Output MEM map coefficients", log = log)
ind = max(0,reff[0].rfind("."))
ofn = params.output_file_name
if (ofn is None) :
ofn = reff[0]+"_mem.mtz" if ind==0 else reff[0][:ind]+"_mem.mtz"
print >> log, " Output file name:", ofn
result.write_mtz_file(file_name = ofn,
column_root_label=params.column_root_label,
d_min=params.output_high_resolution)
broadcast(m="All done", log=log)
return os.path.abspath(ofn)
